Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations46586
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 MiB
Average record size in memory139.0 B

Variable types

Text1
Numeric9

Alerts

categorias_distintas is highly overall correlated with num_publicacionesHigh correlation
log_stock_avg is highly overall correlated with proporcion_usadosHigh correlation
num_publicaciones is highly overall correlated with categorias_distintas and 1 other fieldsHigh correlation
porc_descuento is highly overall correlated with rep_scoreHigh correlation
proporcion_usados is highly overall correlated with log_stock_avgHigh correlation
rep_score is highly overall correlated with num_publicaciones and 1 other fieldsHigh correlation
num_publicaciones is highly skewed (γ1 = 40.81704683) Skewed
seller_nickname has unique values Unique
categorias_distintas has 33233 (71.3%) zeros Zeros
num_publicaciones has 24517 (52.6%) zeros Zeros
porc_descuento has 32431 (69.6%) zeros Zeros
proporcion_refurb has 46228 (99.2%) zeros Zeros
proporcion_usados has 37297 (80.1%) zeros Zeros
rep_score has 14249 (30.6%) zeros Zeros
titulo_length_avg has 1141 (2.4%) zeros Zeros

Reproduction

Analysis started2025-08-04 00:20:39.163145
Analysis finished2025-08-04 00:20:47.032229
Duration7.87 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

seller_nickname
Text

Unique 

Distinct46586
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 MiB
2025-08-03T19:20:47.222218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters465860
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46586 ?
Unique (%)100.0%

Sample

1st row000631669c
2nd row0007153bca
3rd row000bee3c3b
4th row000df2bd02
5th row000e27cea2
ValueCountFrequency (%)
000631669c 1
 
< 0.1%
0032d0112b 1
 
< 0.1%
0085fc93e0 1
 
< 0.1%
002b9cfe2a 1
 
< 0.1%
000bee3c3b 1
 
< 0.1%
000df2bd02 1
 
< 0.1%
000e27cea2 1
 
< 0.1%
000e60a7db 1
 
< 0.1%
0010491a4b 1
 
< 0.1%
0010978f04 1
 
< 0.1%
Other values (46576) 46576
> 99.9%
2025-08-03T19:20:47.465407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 29512
 
6.3%
b 29308
 
6.3%
0 29293
 
6.3%
2 29287
 
6.3%
e 29252
 
6.3%
f 29187
 
6.3%
4 29140
 
6.3%
1 29130
 
6.3%
9 29112
 
6.2%
d 29070
 
6.2%
Other values (6) 173569
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 465860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 29512
 
6.3%
b 29308
 
6.3%
0 29293
 
6.3%
2 29287
 
6.3%
e 29252
 
6.3%
f 29187
 
6.3%
4 29140
 
6.3%
1 29130
 
6.3%
9 29112
 
6.2%
d 29070
 
6.2%
Other values (6) 173569
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 465860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 29512
 
6.3%
b 29308
 
6.3%
0 29293
 
6.3%
2 29287
 
6.3%
e 29252
 
6.3%
f 29187
 
6.3%
4 29140
 
6.3%
1 29130
 
6.3%
9 29112
 
6.2%
d 29070
 
6.2%
Other values (6) 173569
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 465860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 29512
 
6.3%
b 29308
 
6.3%
0 29293
 
6.3%
2 29287
 
6.3%
e 29252
 
6.3%
f 29187
 
6.3%
4 29140
 
6.3%
1 29130
 
6.3%
9 29112
 
6.2%
d 29070
 
6.2%
Other values (6) 173569
37.3%

categorias_distintas
Real number (ℝ)

High correlation  Zeros 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.69896535
Minimum0
Maximum47
Zeros33233
Zeros (%)71.3%
Negative0
Negative (%)0.0%
Memory size364.1 KiB
2025-08-03T19:20:47.547917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum47
Range47
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8362753
Coefficient of variation (CV)2.6271335
Kurtosis65.147393
Mean0.69896535
Median Absolute Deviation (MAD)0
Skewness6.1716084
Sum32562
Variance3.3719071
MonotonicityNot monotonic
2025-08-03T19:20:47.637217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 33233
71.3%
1 6869
 
14.7%
2 2752
 
5.9%
3 1431
 
3.1%
4 714
 
1.5%
5 461
 
1.0%
6 304
 
0.7%
7 176
 
0.4%
8 141
 
0.3%
9 113
 
0.2%
Other values (28) 392
 
0.8%
ValueCountFrequency (%)
0 33233
71.3%
1 6869
 
14.7%
2 2752
 
5.9%
3 1431
 
3.1%
4 714
 
1.5%
5 461
 
1.0%
6 304
 
0.7%
7 176
 
0.4%
8 141
 
0.3%
9 113
 
0.2%
ValueCountFrequency (%)
47 1
 
< 0.1%
40 1
 
< 0.1%
39 1
 
< 0.1%
37 1
 
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
31 2
< 0.1%
29 1
 
< 0.1%
28 3
< 0.1%

log_price_avg
Real number (ℝ)

Distinct27261
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.14760519
Minimum-3.9725662
Maximum9.8688382
Zeros260
Zeros (%)0.6%
Negative23168
Negative (%)49.7%
Memory size364.1 KiB
2025-08-03T19:20:47.720709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.9725662
5-th percentile-0.99269483
Q1-0.43007375
median0
Q30.56992625
95-th percentile1.7478335
Maximum9.8688382
Range13.841404
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.86928561
Coefficient of variation (CV)5.8892618
Kurtosis3.7117961
Mean0.14760519
Median Absolute Deviation (MAD)0.48186021
Skewness1.2741245
Sum6876.3354
Variance0.75565747
MonotonicityNot monotonic
2025-08-03T19:20:47.814900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.4300737469 325
 
0.7%
0 260
 
0.6%
-0.1128113151 209
 
0.4%
0.5699262531 199
 
0.4%
-0.251400811 197
 
0.4%
0.3183077474 187
 
0.4%
-0.4321474642 186
 
0.4%
-0.1115704 181
 
0.4%
-0.1768697461 175
 
0.4%
0.4314401925 172
 
0.4%
Other values (27251) 44495
95.5%
ValueCountFrequency (%)
-3.972566164 1
< 0.1%
-2.512179297 1
< 0.1%
-2.479346959 1
< 0.1%
-2.363964135 1
< 0.1%
-2.356093496 1
< 0.1%
-2.143532561 1
< 0.1%
-2.120888901 1
< 0.1%
-2.081681002 2
< 0.1%
-1.951428245 1
< 0.1%
-1.938867183 1
< 0.1%
ValueCountFrequency (%)
9.868838211 1
< 0.1%
8.467694973 1
< 0.1%
8.2461721 1
< 0.1%
7.150846464 1
< 0.1%
6.607112321 1
< 0.1%
6.426980256 1
< 0.1%
6.289849864 1
< 0.1%
6.15126042 1
< 0.1%
6.038024567 2
< 0.1%
6.038024505 1
< 0.1%

log_stock_avg
Real number (ℝ)

High correlation 

Distinct14300
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19057271
Minimum-0.67532643
Maximum3.5251834
Zeros0
Zeros (%)0.0%
Negative23293
Negative (%)50.0%
Memory size364.1 KiB
2025-08-03T19:20:47.898783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-0.67532643
5-th percentile-0.42243054
Q1-0.42243054
median0
Q30.57756946
95-th percentile1.5362061
Maximum3.5251834
Range4.2005098
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.67283798
Coefficient of variation (CV)3.5306103
Kurtosis1.3382136
Mean0.19057271
Median Absolute Deviation (MAD)0.42243054
Skewness1.2157313
Sum8878.0204
Variance0.45271094
MonotonicityNot monotonic
2025-08-03T19:20:47.988283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.4224305351 12120
26.0%
-0.2744959222 1612
 
3.5%
-0.1695346439 1115
 
2.4%
-0.02160003094 922
 
2.0%
0.199549616 832
 
1.8%
-0.6753264263 828
 
1.8%
-0.08812035142 752
 
1.6%
0.03464209866 428
 
0.9%
0.1647755398 395
 
0.8%
1.008507901 393
 
0.8%
Other values (14290) 27189
58.4%
ValueCountFrequency (%)
-0.6753264263 828
1.8%
-0.6506420035 1
 
< 0.1%
-0.6197677466 1
 
< 0.1%
-0.6121024535 1
 
< 0.1%
-0.599457659 1
 
< 0.1%
-0.5910277959 4
 
< 0.1%
-0.5741680699 1
 
< 0.1%
-0.5663720271 1
 
< 0.1%
-0.5619986405 1
 
< 0.1%
-0.5553118598 1
 
< 0.1%
ValueCountFrequency (%)
3.525183404 5
< 0.1%
3.525176715 1
 
< 0.1%
3.525176107 1
 
< 0.1%
3.525154215 1
 
< 0.1%
3.525150566 1
 
< 0.1%
3.525125023 1
 
< 0.1%
3.525117725 1
 
< 0.1%
3.525114076 1
 
< 0.1%
3.52502405 1
 
< 0.1%
3.524997283 1
 
< 0.1%

num_publicaciones
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct167
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4882583
Minimum0
Maximum710
Zeros24517
Zeros (%)52.6%
Negative0
Negative (%)0.0%
Memory size364.1 KiB
2025-08-03T19:20:48.079762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum710
Range710
Interquartile range (IQR)1

Descriptive statistics

Standard deviation7.2342045
Coefficient of variation (CV)4.8608528
Kurtosis2907.5128
Mean1.4882583
Median Absolute Deviation (MAD)0
Skewness40.817047
Sum69332
Variance52.333714
MonotonicityNot monotonic
2025-08-03T19:20:48.172595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24517
52.6%
0.5 7371
 
15.8%
1 3904
 
8.4%
1.5 2391
 
5.1%
2 1654
 
3.6%
2.5 1129
 
2.4%
3 885
 
1.9%
3.5 673
 
1.4%
4 514
 
1.1%
4.5 433
 
0.9%
Other values (157) 3115
 
6.7%
ValueCountFrequency (%)
0 24517
52.6%
0.5 7371
 
15.8%
1 3904
 
8.4%
1.5 2391
 
5.1%
2 1654
 
3.6%
2.5 1129
 
2.4%
3 885
 
1.9%
3.5 673
 
1.4%
4 514
 
1.1%
4.5 433
 
0.9%
ValueCountFrequency (%)
710 1
< 0.1%
438 1
< 0.1%
437.5 1
< 0.1%
397 1
< 0.1%
254.5 1
< 0.1%
241.5 1
< 0.1%
230.5 1
< 0.1%
214 1
< 0.1%
193.5 1
< 0.1%
191.5 2
< 0.1%

porc_descuento
Real number (ℝ)

High correlation  Zeros 

Distinct7760
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2056225
Minimum0
Maximum16.964343
Zeros32431
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size364.1 KiB
2025-08-03T19:20:48.259599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8.0085928
Maximum16.964343
Range16.964343
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.7107817
Coefficient of variation (CV)2.2484497
Kurtosis7.0934758
Mean1.2056225
Median Absolute Deviation (MAD)0
Skewness2.7144301
Sum56165.131
Variance7.3483373
MonotonicityNot monotonic
2025-08-03T19:20:48.347728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32431
69.6%
1.071428571 441
 
0.9%
2.142857143 205
 
0.4%
5.357142857 169
 
0.4%
1.071428571 150
 
0.3%
4.285714286 135
 
0.3%
3.214285714 120
 
0.3%
1.071428571 107
 
0.2%
1.071428571 107
 
0.2%
8.571428571 103
 
0.2%
Other values (7750) 12618
 
27.1%
ValueCountFrequency (%)
0 32431
69.6%
0.002319109462 1
 
< 0.1%
0.008307376743 1
 
< 0.1%
0.009481668774 1
 
< 0.1%
0.009566326531 1
 
< 0.1%
0.01245847176 1
 
< 0.1%
0.01275510204 1
 
< 0.1%
0.01370044664 1
 
< 0.1%
0.01447876448 1
 
< 0.1%
0.01785714286 1
 
< 0.1%
ValueCountFrequency (%)
16.96434254 1
< 0.1%
16.77020799 1
< 0.1%
16.28621833 1
< 0.1%
16.22894205 1
< 0.1%
16.07118991 1
< 0.1%
15.91849827 1
< 0.1%
15.87301587 1
< 0.1%
15.67221135 1
< 0.1%
15.64288005 1
< 0.1%
15.58928571 1
< 0.1%

proporcion_refurb
Real number (ℝ)

Zeros 

Distinct51
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0055426079
Minimum0
Maximum1
Zeros46228
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size364.1 KiB
2025-08-03T19:20:48.430346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.070000831
Coefficient of variation (CV)12.629584
Kurtosis181.50129
Mean0.0055426079
Median Absolute Deviation (MAD)0
Skewness13.371624
Sum258.20793
Variance0.0049001163
MonotonicityNot monotonic
2025-08-03T19:20:48.508729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46228
99.2%
1 199
 
0.4%
0.5 34
 
0.1%
0.3333333333 14
 
< 0.1%
0.25 12
 
< 0.1%
0.6666666667 12
 
< 0.1%
0.2 10
 
< 0.1%
0.6 4
 
< 0.1%
0.875 4
 
< 0.1%
0.1666666667 4
 
< 0.1%
Other values (41) 65
 
0.1%
ValueCountFrequency (%)
0 46228
99.2%
0.0007037297678 1
 
< 0.1%
0.01282051282 1
 
< 0.1%
0.015625 1
 
< 0.1%
0.01694915254 1
 
< 0.1%
0.01886792453 1
 
< 0.1%
0.02272727273 1
 
< 0.1%
0.03703703704 1
 
< 0.1%
0.03846153846 1
 
< 0.1%
0.05555555556 1
 
< 0.1%
ValueCountFrequency (%)
1 199
0.4%
0.9285714286 1
 
< 0.1%
0.875 4
 
< 0.1%
0.8 2
 
< 0.1%
0.75 4
 
< 0.1%
0.7454545455 1
 
< 0.1%
0.7272727273 1
 
< 0.1%
0.7142857143 2
 
< 0.1%
0.6666666667 12
 
< 0.1%
0.6363636364 1
 
< 0.1%

proporcion_usados
Real number (ℝ)

High correlation  Zeros 

Distinct97
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.19075488
Minimum0
Maximum1
Zeros37297
Zeros (%)80.1%
Negative0
Negative (%)0.0%
Memory size364.1 KiB
2025-08-03T19:20:48.589056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.38912952
Coefficient of variation (CV)2.0399453
Kurtosis0.51100484
Mean0.19075488
Median Absolute Deviation (MAD)0
Skewness1.5761208
Sum8886.5068
Variance0.15142178
MonotonicityNot monotonic
2025-08-03T19:20:48.672465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37297
80.1%
1 8580
 
18.4%
0.5 199
 
0.4%
0.3333333333 86
 
0.2%
0.6666666667 59
 
0.1%
0.25 43
 
0.1%
0.2 34
 
0.1%
0.75 27
 
0.1%
0.1666666667 26
 
0.1%
0.8 21
 
< 0.1%
Other values (87) 214
 
0.5%
ValueCountFrequency (%)
0 37297
80.1%
0.004504504505 1
 
< 0.1%
0.009259259259 1
 
< 0.1%
0.015625 1
 
< 0.1%
0.02040816327 1
 
< 0.1%
0.02083333333 1
 
< 0.1%
0.02173913043 1
 
< 0.1%
0.0243902439 1
 
< 0.1%
0.02564102564 1
 
< 0.1%
0.02857142857 1
 
< 0.1%
ValueCountFrequency (%)
1 8580
18.4%
0.9655172414 1
 
< 0.1%
0.9615384615 1
 
< 0.1%
0.9565217391 1
 
< 0.1%
0.9523809524 1
 
< 0.1%
0.9285714286 1
 
< 0.1%
0.9189189189 1
 
< 0.1%
0.9166666667 2
 
< 0.1%
0.9032258065 1
 
< 0.1%
0.9 2
 
< 0.1%

rep_score
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.090642396
Minimum-1
Maximum0.66666667
Zeros14249
Zeros (%)30.6%
Negative14812
Negative (%)31.8%
Memory size364.1 KiB
2025-08-03T19:20:48.738400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.66666667
median0
Q30.33333333
95-th percentile0.66666667
Maximum0.66666667
Range1.6666667
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5516445
Coefficient of variation (CV)-6.0859435
Kurtosis-0.9676621
Mean-0.090642396
Median Absolute Deviation (MAD)0.33333333
Skewness-0.50824247
Sum-4222.6667
Variance0.30431166
MonotonicityNot monotonic
2025-08-03T19:20:48.793099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 14249
30.6%
0.3333333333 11749
25.2%
-1 8948
19.2%
0.6666666667 5776
12.4%
-0.6666666667 3261
 
7.0%
-0.3333333333 2603
 
5.6%
ValueCountFrequency (%)
-1 8948
19.2%
-0.6666666667 3261
 
7.0%
-0.3333333333 2603
 
5.6%
0 14249
30.6%
0.3333333333 11749
25.2%
0.6666666667 5776
12.4%
ValueCountFrequency (%)
0.6666666667 5776
12.4%
0.3333333333 11749
25.2%
0 14249
30.6%
-0.3333333333 2603
 
5.6%
-0.6666666667 3261
 
7.0%
-1 8948
19.2%

titulo_length_avg
Real number (ℝ)

Zeros 

Distinct3117
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.25284388
Minimum-4.0458015
Maximum11.068702
Zeros1141
Zeros (%)2.4%
Negative22716
Negative (%)48.8%
Memory size364.1 KiB
2025-08-03T19:20:48.864855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-4.0458015
5-th percentile-2.2137405
Q1-0.69465649
median0
Q30.30534351
95-th percentile0.73282443
Maximum11.068702
Range15.114504
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0551889
Coefficient of variation (CV)-4.1732825
Kurtosis9.5257186
Mean-0.25284388
Median Absolute Deviation (MAD)0.38167939
Skewness0.63216099
Sum-11778.985
Variance1.1134237
MonotonicityNot monotonic
2025-08-03T19:20:48.950629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4580152672 3690
 
7.9%
0.3816793893 2399
 
5.1%
0.3053435115 2056
 
4.4%
0.2290076336 1744
 
3.7%
0.1526717557 1434
 
3.1%
0.07633587786 1284
 
2.8%
0 1141
 
2.4%
-0.07633587786 969
 
2.1%
-0.1526717557 899
 
1.9%
-0.2290076336 767
 
1.6%
Other values (3107) 30203
64.8%
ValueCountFrequency (%)
-4.045801527 1
 
< 0.1%
-3.969465649 1
 
< 0.1%
-3.893129771 3
 
< 0.1%
-3.816793893 11
 
< 0.1%
-3.740458015 18
 
< 0.1%
-3.664122137 20
< 0.1%
-3.58778626 34
0.1%
-3.511450382 35
0.1%
-3.435114504 33
0.1%
-3.358778626 46
0.1%
ValueCountFrequency (%)
11.06870229 3
< 0.1%
10.99236641 3
< 0.1%
10.76335878 2
< 0.1%
10.6870229 1
 
< 0.1%
10.61068702 1
 
< 0.1%
10.53435115 1
 
< 0.1%
9.847328244 1
 
< 0.1%
9.770992366 2
< 0.1%
9.618320611 2
< 0.1%
9.465648855 1
 
< 0.1%

Interactions

2025-08-03T19:20:46.116951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:40.010562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-08-03T19:20:41.856095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:42.483557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:43.159837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:43.875226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:44.496286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:45.165446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-08-03T19:20:42.391091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:43.081557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:43.753308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:44.422846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:45.098883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-08-03T19:20:45.732651image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-08-03T19:20:49.013057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
categorias_distintaslog_price_avglog_stock_avgnum_publicacionesporc_descuentoproporcion_refurbproporcion_usadosrep_scoretitulo_length_avg
categorias_distintas1.000-0.1660.2330.7160.2760.007-0.1950.4110.179
log_price_avg-0.1661.000-0.372-0.141-0.2910.0640.322-0.332-0.155
log_stock_avg0.233-0.3721.0000.2350.378-0.024-0.5090.4170.269
num_publicaciones0.716-0.1410.2351.0000.2640.023-0.2250.5250.170
porc_descuento0.276-0.2910.3780.2641.0000.004-0.3110.5010.291
proporcion_refurb0.0070.064-0.0240.0230.0041.000-0.0210.0100.001
proporcion_usados-0.1950.322-0.509-0.225-0.311-0.0211.000-0.414-0.315
rep_score0.411-0.3320.4170.5250.5010.010-0.4141.0000.320
titulo_length_avg0.179-0.1550.2690.1700.2910.001-0.3150.3201.000

Missing values

2025-08-03T19:20:46.845376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-08-03T19:20:46.943863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

seller_nicknamecategorias_distintaslog_price_avglog_stock_avgnum_publicacionesporc_descuentoproporcion_refurbproporcion_usadosrep_scoretitulo_length_avg
0000631669c0.00.1790970.1995500.00.0000000.00.0-1.000000-2.900763
10007153bca0.0-0.2514010.5463860.50.0000000.00.00.0000000.458015
2000bee3c3b0.0-0.394075-0.6753260.50.0000000.00.0-1.000000-2.366412
3000df2bd020.00.590278-0.0216000.00.0000000.01.00.000000-1.984733
4000e27cea21.0-0.208310-0.1813080.50.0000000.00.00.3333330.458015
5000e60a7db6.0-0.9735491.3254993.512.4018600.00.00.6666670.362595
60010491a4b0.02.077369-0.4224310.00.0000000.00.0-1.000000-1.450382
70010978f041.0-0.9498780.9410830.510.9285710.00.00.333333-0.877863
80012fdce4a0.00.548671-0.2744960.00.0000000.00.0-0.6666670.000000
900143ac49b1.00.011142-0.2959830.50.0000000.00.0-0.6666670.458015
seller_nicknamecategorias_distintaslog_price_avglog_stock_avgnum_publicacionesporc_descuentoproporcion_refurbproporcion_usadosrep_scoretitulo_length_avg
46576fff33fa5bf1.01.202388-0.2552750.51.0714290.00.00.0000001.030534
46577fff3ac98651.0-0.0561930.7363740.50.0000000.00.00.0000000.648855
46578fff98c73f40.0-0.384195-0.4224310.00.0000000.00.00.3333330.458015
46579fff99199fa1.0-0.1938920.8091450.54.2857930.00.00.3333330.381679
46580fff9f4c6a00.02.178301-0.4224310.00.0000000.00.0-1.000000-3.816794
46581fffac55ae40.0-0.0536160.0346420.00.0000000.00.0-0.6666676.717557
46582fffbc920831.0-0.0299950.7815742.03.6442180.00.00.6666671.740458
46583fffd1017390.02.178270-0.4224310.00.0000000.00.00.0000000.381679
46584fffe8e78c15.0-0.8119620.9777403.511.3305070.00.00.6666671.383588
46585ffff4071000.00.2987690.2312960.00.0000000.00.00.3333330.381679